Turning Customer Voices into Strategic Insight
To stay ahead in a fast-moving market, product teams rely on continuous feedback loops to enhance product relevance and tackle their customers’ biggest pain points.
However, this requires continuously triaging an overwhelming volume of feedback to uncover key insights and emerging trends. It’s a familiar story for many product leaders.
“Every month,” Amir explains, “we receive hundreds of customer feedback scattered across support tickets, feature requests, surveys, and forums. My team spends countless hours just trying to figure out what really matters. We can’t easily spot patterns or tell whether the same pain point is coming from multiple customers or a specific industry.”
Addressing this challenge would need three things to come together at once: advances in AI, deep expertise in the customer experience domain, and new techniques to apply the AI to that domain.
In a pivotal conversation with Yoav, a peer working on a core part of Azure’s infrastructure, Amir had a eureka moment. It revealed the potential to transmute scattered feedback into a wealth of strategic guidance for product teams.
They explored how employing AI embedding technologies with semantic clustering techniques could programmatically apply Amir’s domain expertise could empower product leaders. This realization led to an idea. They could connect the dots across diverse customer input, showing product leaders a clear picture of what customers need.
Fueling Innovation
Amir brought the idea to Ady Mor-Biran, Director of The Garage IMEA—India, Middle East, and Africa.
“This project team followed every validation step of The Garage Growth Framework rigorously,” said Ady. “They were a textbook example of the right way to innovate.”
The Garage played a pivotal role in the project’s journey providing a dynamic environment for creativity, collaboration, and experimentation. Through initiatives like Garage Ventures and the Global Hackathon, the team rapidly prototyped, tested, and refined their solution, benefiting from mentorship, resources, and exposure to diverse perspectives.
These programs accelerated development and connected the project with leaders who could use it.
Amir and Yoav built a prototype that used AI to convert raw customer feedback into user story format, then applied the K-means algorithm to cluster similar feedback.
“When we first saw the top feedback themes automatically surfaced and prioritized by customer volume,” said Amir, “it was a breakthrough moment for the team. I literally said ‘wow.’ We’d never had that kind of visibility before. It was the first time we could actually see what mattered most to our customers and clearly connect individual customer voices to the bigger product story.”
For the first time, product leaders could instantly see the main themes and pain points emerging from thousands of feedback entries, without the need for manual triage, affinitizing, and clustering.
Impact: Empowering Product Leaders, Transforming Decisions
The response from product leaders was immediate and enthusiastic.
With CX Observe Product Feedback Copilot, product leaders could finally identify key customer pain points, justify investments, and prioritize their roadmaps with confidence. The tool’s public preview reduced duplicate efforts and enabled more strategic planning, directly impacting how Microsoft’s Azure teams deliver greater value to customers. By transforming feedback into action, this Copilot helps Microsoft Azure customers achieve more.
CX Observe Product Feedback Copilot is more than a tool. It’s a testament to the power of curiosity, collaboration, and the belief that technology can make a difference where it matters most.